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a. Selection: Depending on the two classes chosen, the demographics of the school itself can greatly influence the outcome of the experiment due to goals. Both classes belonged to a small public secondary school. Depending on who the subjects are, the outcome could be seen as different.
c. Mortality: The dropping out of subjects can lead to an overall attrition but should not have an impact on the internal validity of the experiment. As long as the control group is consistent within the rest of the experiment, people dropping out only lessons the subject amount and not the quality of the subjects.
d. Regression: This has to do with aiming towards to average. The people with the lowest score aim to get a higher mark because they can only “get better”. Instead of looking at it from and “improvement” standpoint, it is important to view the subjects as making gradual strides to improve instead of an obvious jump.
e. Testing: If you repeatedly test a student, this could easily lead to a bias that causes change within the experiment. Subjects may remember the correct answer from previous questions and therefore, they are not coming from an unbiased perspective but instead, using memory to help them get through. Also, sometimes too much testing does not give enough room for actual growth.
f. Instrumentation: Depending on what instruments or manipulatives is used during the experiment, the outcome can be different. The Partial experiment is different from the full experiment due to its implementations.
g. History: History can affect the outcome because students are affected every day by their environment and therefore, without the control of the variables, nothing is consistent. This can greatly affect the experiment as history changes perspective.
The findings of the study are that the pupils involved in the “full experiment” and the partial experiment scored differently due to exposure of manipulatives and
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